tf_executor.fetch
  }
  func.return
}

// -----

// Tests one group with multiple branches.
// We expect the following dependency chains after the pass
// A -> B -> fetch, C -> D -> fetch, E -> fetch.
func.func @one_group_multiple_branches() {
  tf_executor.graph {
    // CHECK: %[[control:.*]] = tf_executor.island wraps "tf.A"()

  // CHECK: [[out_ch:%.*]] = tfrt.merge.chains [[cond_res]]#0, %arg0 : !tfrt.chain, !tfrt.chain
  // CHECK: tfrt.return [[out_ch]], [[cond_res]]#1 : !tfrt.chain, !tfrt_fallback.tf_tensor
  func.return %2 : tensor<i32>
}

// CHECK-LABEL: func @cond_stateful(%arg0: !tfrt.chain, %arg1: !tfrt_fallback.tf_tensor) -> (!tfrt.chain, !tfrt_fallback.tf_tensor)
func.func @cond_stateful(%arg0: tensor<i32>) -> tensor<i32> {

Of all the found transform chains, Gradle tries to select the best one:

- If there is only one transform chain, it is selected.
- If there are two transform chains, and one is a suffix of the other one, it is selected.
- If there is a shortest transform chain, then it is selected.
- In all other cases, the selection fails and an error is reported.

        }

        // We found no matches. Attempt to construct artifact transform chains which produce matching variants.
        List<TransformedVariant> transformedVariants = consumerProvidedVariantFinder.findTransformedVariants(variants, componentRequested);

)

// MTLSSettings describes the mTLS options for a filter chain
type MTLSSettings struct {
	// Port is the port this option applies for
	Port uint32
	// Mode is the mTLS  mode to use
	Mode model.MutualTLSMode
	// TCP describes the tls context to use for TCP filter chains
	TCP *tlsv3.DownstreamTlsContext
	// HTTP describes the tls context to use for HTTP filter chains
	HTTP *tlsv3.DownstreamTlsContext
}

[[sec:cpp_supported_tool_chain]]
=== Supported tool chain

Gradle offers the ability to execute the same build using different tool chains.
When you build a native binary, Gradle will attempt to locate a tool chain installed on your machine that can build the binary.
Gradle select the first tool chain that can build for the target operating system and architecture.

        is FunctionCall -> run {
            val errors = mutableListOf<DocumentError>()
            // Check for receiver: if it is a complex expression, it cannot be expressed in a DOM; but we can handle access chains as chained names
            val name = when (expr.receiver) {
                null -> expr.name
                is PropertyAccess ->
                    expr.receiver.asChainedNameOrNull()?.plus(".${expr.name}") ?: run {

  return true;
}

// Populates `chain_resource_to_ops_map`, the map from all resources that need
// to be chained to the set of operations that access the resource, and
// `resource_equivalence_classes`. Resources are equivalent if they are accessed
// by a common op, and equivalent resources will be assigned to the same chain.
void CollectChainResources(
    func::FuncOp func, ResourceToOpsMapTy& chain_resource_to_ops_map,

Pipelines

A pipeline is a possibly chained sequence of "commands". A command is a simple
value (argument) or a function or method call, possibly with multiple arguments:

	Argument
		The result is the value of evaluating the argument.
	.Method [Argument...]
		The method can be alone or the last element of a chain but,
		unlike methods in the middle of a chain, it can take arguments.

			if k == model.VirtualInboundListenerName && v != 3 {
				t.Fatalf("expect virtual listener has 3 passthrough filter chains, found %d", v)
			}
			if k == model.VirtualInboundCatchAllHTTPFilterChainName && v != 2 {
				t.Fatalf("expect virtual listener has 2 passthrough filter chains, found %d", v)
			}
		}

		if tt.useExactBalance {